Early-stage detection of cracks in large civil, offshore, and aerospace structures is of a crucial importance for (i) estimation of the remaining service life, and (ii) assuring safety of these structures. Cracks are not limited to, but mainly due to fatigue loading, e.g. traffic load on a bridge. The structures/structural components of interest for monitoring are made of thin-walled components i.e. a structure having a thickness which is significantly smaller than its other two dimensions. For such structures, acoustic emission (AE) is one of the most widely-used crack monitoring techniques consequent to (i) having a relatively large coverage area, (ii) being sensitive to small cracks, even at the initiation phase, and (iii) reasonably low implantation costs. Acoustic emission systems work based on the fact that the activity of structural defects release acoustic energy signals propagating inside and on the surface of the structure as guided wave (GW) modes in thin-walled structures, mainly the fundamental symmetric Lamb wave S0 and the fundamental antisymmetric lamb wave A0. Typically, the S0 waves travel at a higher speed than the A0 waves. To find the location of an AE source, e.g. an active crack, in the conventional triangulation-based AE approach, synchronized measurements from at least tree sensor locations are required. The typical frequency range of AE signals is [10 kHz-1 MHz], demanding sampling rates up to a few mega-samples per second. It is believed that three main issues have hindered the growth rate of AE techniques for monitoring large scale structures, as listed below.
1. Required sensor network. The main challenges include the communication, synchronization, and connection of a large number of sensors to a central processing unit.
2. Storage, aggregation, and forwarding of enormous amount of data, being recorded at the mentioned sampling rates for duration of the monitoring, e.g. a few months.
3. Complexity of AE signals and substantial uncertainty in their interpretation coming from (i) multimode nature of guided waves (GW) in thin-walled structures, (ii) dispersion of guided waves, (iii) geometrical spreading, (iv) different attenuation behavior for different GW modes, (v) environmental noise, and (vi) reflection and refraction of GW due to interaction with structural entities, e.g. stiffeners.
In addition to these difficulties, yet existing AE methods do not provide reliable quantitative information about the cracks, e.g. length and depth. In U.S. Pat. No. 5,929,315 an AE method and apparatus is disclosed for detecting and measuring cracks in plate-like structures. A false aperture transducer is designed to provide a criterion for filtering out extraneous noise in AE signals by computing the ratio of the high-frequency peak amplitude to low-frequency peak amplitude. A calibration curve correlating crack depth to the amplitude ratio was obtained by (i) simulating crack growth in a fracture specimen coupled to a test structure or field structure, and (ii) measuring acoustic emission signal in the structure by the false aperture transducer. The calibration curve correlates simulated crack depth percentage with computed peak amplitude ratio of the measured signal. Location of a crack-like source can be determined by detecting the AE signal from three different locations and ascertaining the point of intersection.
In the referenced disclosure, wave modes are separated in accordance with frequency filtering, i.e. a high-pass (>100 kHz) and band-pass (20-80 kHz) frequency filter for in-plane and out-of-plane waves. The disclosure relies on non-dispersive propagation of ‘flexural wave modes’ which have differing ratios for out of plane and in-plane motions. However, the method proposed suffers from practical limitations since multiple wave modes can exist in the entire frequency-band (>20 kHz), and the amplitudes in the above-mentioned ranges are not generally representative for the assumed wave mode. It is not physically realistic that the wave modes propagate at predetermined speeds in a non-dispersive manner. The invention has therefore as an object to improve the reliability of crack detection and growth monitoring, that the prior art fails to resolve. In addition, through its novel formulation, the three issues listed earlier on the application of AE for large-scale structures may be overcome, i.e. the complex sensor network, large amount of data for storage and forwarding, complexities of guided wave signals.